Best Practices in Risk Management for Securitized Products
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Analysis of Securitized Asset Liquidity June 2017 an He and Bruce Mizrach1
Analysis of Securitized Asset Liquidity June 2017 An He and Bruce Mizrach1 1. Introduction This research note extends our prior analysis2 of corporate bond liquidity to the structured products markets. We analyze data from the TRACE3 system, which began collecting secondary market trading activity on structured products in 2011. We explore two general categories of structured products: (1) real estate securities, including mortgage-backed securities in residential housing (MBS) and commercial building (CMBS), collateralized mortgage products (CMO) and to-be-announced forward mortgages (TBA); and (2) asset-backed securities (ABS) in credit cards, autos, student loans and other miscellaneous categories. Consistent with others,4 we find that the new issue market for securitized assets decreased sharply after the financial crisis and has not yet rebounded to pre-crisis levels. Issuance is below 2007 levels in CMBS, CMOs and ABS. MBS issuance had recovered by 2012 but has declined over the last four years. By contrast, 2016 issuance in the corporate bond market was at a record high for the fifth consecutive year, exceeding $1.5 trillion. Consistent with the new issue volume decline, the median age of securities being traded in non-agency CMO are more than ten years old. In student loans, the average security is over seven years old. Over the last four years, secondary market trading volumes in CMOs and TBA are down from 14 to 27%. Overall ABS volumes are down 16%. Student loan and other miscellaneous ABS declines balance increases in automobiles and credit cards. By contrast, daily trading volume in the most active corporate bonds is up nearly 28%. -
Basel III: Post-Crisis Reforms
Basel III: Post-Crisis Reforms Implementation Timeline Focus: Capital Definitions, Capital Focus: Capital Requirements Buffers and Liquidity Requirements Basel lll 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 1 January 2022 Full implementation of: 1. Revised standardised approach for credit risk; 2. Revised IRB framework; 1 January 3. Revised CVA framework; 1 January 1 January 1 January 1 January 1 January 2018 4. Revised operational risk framework; 2027 5. Revised market risk framework (Fundamental Review of 2023 2024 2025 2026 Full implementation of Leverage Trading Book); and Output 6. Leverage Ratio (revised exposure definition). Output Output Output Output Ratio (Existing exposure floor: Transitional implementation floor: 55% floor: 60% floor: 65% floor: 70% definition) Output floor: 50% 72.5% Capital Ratios 0% - 2.5% 0% - 2.5% Countercyclical 0% - 2.5% 2.5% Buffer 2.5% Conservation 2.5% Buffer 8% 6% Minimum Capital 4.5% Requirement Core Equity Tier 1 (CET 1) Tier 1 (T1) Total Capital (Tier 1 + Tier 2) Standardised Approach for Credit Risk New Categories of Revisions to the Existing Standardised Approach Exposures • Exposures to Banks • Exposure to Covered Bonds Bank exposures will be risk-weighted based on either the External Credit Risk Assessment Approach (ECRA) or Standardised Credit Risk Rated covered bonds will be risk Assessment Approach (SCRA). Banks are to apply ECRA where regulators do allow the use of external ratings for regulatory purposes and weighted based on issue SCRA for regulators that don’t. specific rating while risk weights for unrated covered bonds will • Exposures to Multilateral Development Banks (MDBs) be inferred from the issuer’s For exposures that do not fulfil the eligibility criteria, risk weights are to be determined by either SCRA or ECRA. -
Asset Securitization
L-Sec Comptroller of the Currency Administrator of National Banks Asset Securitization Comptroller’s Handbook November 1997 L Liquidity and Funds Management Asset Securitization Table of Contents Introduction 1 Background 1 Definition 2 A Brief History 2 Market Evolution 3 Benefits of Securitization 4 Securitization Process 6 Basic Structures of Asset-Backed Securities 6 Parties to the Transaction 7 Structuring the Transaction 12 Segregating the Assets 13 Creating Securitization Vehicles 15 Providing Credit Enhancement 19 Issuing Interests in the Asset Pool 23 The Mechanics of Cash Flow 25 Cash Flow Allocations 25 Risk Management 30 Impact of Securitization on Bank Issuers 30 Process Management 30 Risks and Controls 33 Reputation Risk 34 Strategic Risk 35 Credit Risk 37 Transaction Risk 43 Liquidity Risk 47 Compliance Risk 49 Other Issues 49 Risk-Based Capital 56 Comptroller’s Handbook i Asset Securitization Examination Objectives 61 Examination Procedures 62 Overview 62 Management Oversight 64 Risk Management 68 Management Information Systems 71 Accounting and Risk-Based Capital 73 Functions 77 Originations 77 Servicing 80 Other Roles 83 Overall Conclusions 86 References 89 ii Asset Securitization Introduction Background Asset securitization is helping to shape the future of traditional commercial banking. By using the securities markets to fund portions of the loan portfolio, banks can allocate capital more efficiently, access diverse and cost- effective funding sources, and better manage business risks. But securitization markets offer challenges as well as opportunity. Indeed, the successes of nonbank securitizers are forcing banks to adopt some of their practices. Competition from commercial paper underwriters and captive finance companies has taken a toll on banks’ market share and profitability in the prime credit and consumer loan businesses. -
Personal Loans 101: Understanding Your Credit Risk Loans Have Some Risk for Both the Borrower and the Lender
PERSONAL LOANS 101: Understanding YoUr credit risk Loans have some risk for both the borrower and the lender. The borrower takes on the responsibilities and terms of paying back the loan. The lender’s risk is the chance of non-payment. Consumers can choose from several types of loans. As a borrower, you need to understand the type of loan you are considering and its possible risk. This brochure provides information to help you make a smart choice before applying for a loan. 2 It is important to review your financial situation to see if you can handle another monthly payment before applying for a loan. Creating a budget will help you apply for the loan that best meets your present and future needs. For an interactive budget, visit www.afsaef.org/budgetplanner or www.afsaef.org/personalloans101. You will need to show the lender that you can repay what you borrow, with interest. After you have made a budget, consider these factors, which maY redUce or add risk to a Loan. 3 abiLitY to repaY the Loan Is the lender evaluating your ability to repay the loan based on facts such as your credit history, current and expected income, current expenses, debt-to- income ratio (your expenses compared to your income) and employment status? This assessment, often called underwriting, helps determine if you can make the monthly payment and raises your chances of getting a loan to fit your needs that you can afford to repay. It depends on you providing complete and correct information to the lender. Testing “your ability to repay” and appropriate “underwriting” reduces your risk when taking out any type of loan. -
Operational Risk Management Guide
OPERATIONAL RISK MANAGEMENT GUIDE U.S. DEPARTMENT OF AGRICULTURE FOREST SERVICE 2020 Last Updated 02/26/2020 RISK MANAGEMENT COUNCIL IN COOPERATION WITH THE OFFICE OF SAFETY & OCCUPATIONAL HEALTH and THE NATIONAL AVIATION SAFETY COUNCIL Contents Contents ....................................................................................................................................................................................... 2 Executive Summary .................................................................................................................................................................. i Introduction ............................................................................................................................................................................... 1 What is Operational Risk Management? ................................................................................................................... 1 The Terminology of ORM ................................................................................................................................................ 1 Principles of ORM Application ........................................................................................................................................... 6 The Five-Step ORM Process ................................................................................................................................................ 7 Step 1: Identify Hazards .................................................................................................................................................. -
Hedge Performance: Insurer Market Penetration and Basis Risk
CORE Metadata, citation and similar papers at core.ac.uk Provided by Research Papers in Economics This PDF is a selection from an out-of-print volume from the National Bureau of Economic Research Volume Title: The Financing of Catastrophe Risk Volume Author/Editor: Kenneth A. Froot, editor Volume Publisher: University of Chicago Press Volume ISBN: 0-226-26623-0 Volume URL: http://www.nber.org/books/froo99-1 Publication Date: January 1999 Chapter Title: Index Hedge Performance: Insurer Market Penetration and Basis Risk Chapter Author: John Major Chapter URL: http://www.nber.org/chapters/c7956 Chapter pages in book: (p. 391 - 432) 10 Index Hedge Performance: Insurer Market Penetration and Basis Risk John A. Major Index-based financial instruments bring transparency and efficiency to both sides of risk transfer, to investor and hedger alike. Unfortunately, to the extent that an index is anonymous and commoditized, it cannot correlate perfectly with a specific portfolio. Thus, hedging with index-based financial instruments brings with it basis risk. The result is “significant practical and philosophical barriers” to the financing of propertykasualty catastrophe risks by means of catastrophe derivatives (Foppert 1993). This study explores the basis risk be- tween catastrophe futures and portfolios of insured homeowners’ building risks subject to the hurricane peril.’ A concrete example of the influence of market penetration on basis risk can be seen in figures 10.1-10.3. Figure 10.1 is a map of the Miami, Florida, vicin- John A. Major is senior vice president at Guy Carpenter and Company, Inc. He is an Associate of the Society of Actuaries. -
Asset Pricing with Liquidity Risk∗
Asset Pricing with Liquidity Risk∗ Viral V. Acharyay and Lasse Heje Pedersenz First Version: July 10, 2000 Current Version: September 24, 2004 Abstract This paper solves explicitly an equilibrium asset pricing model with liq- uidity risk — the risk arising from unpredictable changes in liquidity over time. In our liquidity-adjusted capital asset pricing model, a security's re- quired return depends on its expected liquidity as well as on the covariances of its own return and liquidity with market return and market liquidity. In addition, the model shows how a negative shock to a security's liquidity, if it is persistent, results in low contemporaneous returns and high predicted future returns. The model provides a simple, unified framework for under- standing the various channels through which liquidity risk may affect asset prices. Our empirical results shed light on the total and relative economic significance of these channels. ∗We are grateful for conversations with Andrew Ang, Joseph Chen, Sergei Davydenko, Fran- cisco Gomes, Joel Hasbrouck, Andrew Jackson, Tim Johnson, Martin Lettau, Anthony Lynch, Stefan Nagel, Lubos Pastor, Tano Santos, Dimitri Vayanos, Luis Viceira, Jeff Wurgler, and semi- nar participants at London Business School, London School of Economics, New York University, the National Bureau of Economic Research (NBER) Summer Institute 2002, the Five Star Confer- ence 2002, Western Finance Association Meetings 2003, and the Texas Finance Festival 2004. We are especially indebted to Yakov Amihud and to an anonymous referee for help and many valuable suggestions. All errors remain our own. yAcharya is at London Business School and is a Research Affiliate of the Centre for Eco- nomic Policy Research (CEPR). -
Revised Standards for Minimum Capital Requirements for Market Risk by the Basel Committee on Banking Supervision (“The Committee”)
A revised version of this standard was published in January 2019. https://www.bis.org/bcbs/publ/d457.pdf Basel Committee on Banking Supervision STANDARDS Minimum capital requirements for market risk January 2016 A revised version of this standard was published in January 2019. https://www.bis.org/bcbs/publ/d457.pdf This publication is available on the BIS website (www.bis.org). © Bank for International Settlements 2015. All rights reserved. Brief excerpts may be reproduced or translated provided the source is stated. ISBN 978-92-9197-399-6 (print) ISBN 978-92-9197-416-0 (online) A revised version of this standard was published in January 2019. https://www.bis.org/bcbs/publ/d457.pdf Minimum capital requirements for Market Risk Contents Preamble ............................................................................................................................................................................................... 5 Minimum capital requirements for market risk ..................................................................................................................... 5 A. The boundary between the trading book and banking book and the scope of application of the minimum capital requirements for market risk ........................................................................................................... 5 1. Scope of application and methods of measuring market risk ...................................................................... 5 2. Definition of the trading book .................................................................................................................................. -
Credit Risk Models
Lecture notes on risk management, public policy, and the financial system Credit risk models Allan M. Malz Columbia University Credit risk models Outline Overview of credit risk analytics Single-obligor credit risk models © 2020 Allan M. Malz Last updated: February 8, 2021 2/32 Credit risk models Overview of credit risk analytics Overview of credit risk analytics Credit risk metrics and models Intensity models and default time analytics Single-obligor credit risk models 3/32 Credit risk models Overview of credit risk analytics Credit risk metrics and models Key metrics of credit risk Probability of default πt defined over a time horizon t, e.g. one year Exposure at default: amount the lender can lose in default For a loan or bond, par value plus accrued interest For OTC derivatives, also driven by market value Net present value (NPV) 0 ( counterparty risk) S → But exposure at default 0 ≥ Recovery: creditor generally loses fraction of exposure R < 100 percent Loss given default (LGD) equals exposure minus recovery (a fraction 1 − R) Expected loss (EL) equals default probability × LGD or fraction πt × (1 − R) Credit risk management focuses on unexpected loss Credit Value-at-Risk related to a quantile of the credit return distribution Differs from market risk in excluding EL Credit VaR at confidence level of α defined as: 1 − α-quantile of credit loss distribution − EL 4/32 Credit risk models Overview of credit risk analytics Credit risk metrics and models Estimating default probabilities Risk-neutral default probabilities based on market -
Risk Parity an Alternative Approach to Asset Allocation
FEATURE Risk Parity An Alternative Approach to Asset Allocation Alexander Pekker, PhD, CFA®, ASA, Meghan P. Elwell, JD, AIFA®, and Robert G. Smith III, CIMC®, AIF® ollowing the financial crisis of tors, traditional RP strategies fall short respectively, but a rather high Sharpe 2008, many members of the of required return targets and leveraged ratio, 0.86. In other words, while the investment management com- RP strategies do not provide enough portfolio is unlikely to meet the expected F munity, including Sage,intensified their potential benefits to outweigh their return target of many institutional inves- scrutiny of mean-variance optimization risks. Instead we advocate a liability- tors (say, 7 percent or higher), its effi- (MVO) and modern portfolio theory based approach that incorporates risk ciency, or “bang for the buck” (i.e., return (MPT) as the bedrock of asset alloca- budgeting, a key theme of RP, as well as per unit of risk, in excess of the risk-free tion (Elwell and Pekker 2010). Among tactical asset allocation. rate), is quite strong. various alternative approaches to asset How does this sample RP portfo- What is Risk Parity? allocation, risk parity (RP) has been in the lio compare with a sample MVO port- news lately (e.g., Nauman 2012; Summers As noted above, an RP portfolio is one folio? A sample MVO portfolio with a 2012), especially as some hedge funds, where risk, defined as standard deviation return target of 7 percent is shown in such as AQR, and large plan sponsors, of returns, is distributed evenly among table 2. Unlike the sample RP portfolio, such as the San Diego County Employees all potential asset classes;1 table 1 shows the MVO portfolio is heavily allocated Retirement Association, have advocated a sample (unleveraged) RP portfolio toward equities, and it has much higher its adoption. -
The Market Risk Premium: Expectational Estimates Using Analysts' Forecasts
The Market Risk Premium: Expectational Estimates Using Analysts' Forecasts Robert S. Harris and Felicia C. Marston Us ing expectatwnal data from f711a11cial a 11 a~r.11s. we e~ t ima t e a market risk premium for US stocks. Using the S&P 500 a.1 a pro1·1•.fin· the market portfolio. the Lll'erage market risk premium i.lfound to be 7. 14% abo1·e yields on /o11g-ter111 US go1·ern 111 e11t honds m·er the period I 982-l 99X. This ri~k premium 1•aries over time; much oft his 1·aria1io11 can he explained by either I he /e1 1el ofi11teres1 mies or readily availahle fonrard-looking proxies for ri.~k . Th e marke1 ri.1k p remium appears to 111 onz inversely with gol'ern111 e11 t interes1 ra/es .rngges1i11g Iha/ required rerurns 011 .~locks are more stable than interest rates themse!Pes. {JEL: GJI. G l 2] Sfhc notion of a market ri sk premium (th e spread choice has some appealing chara cteri sti cs but is between in vestor required returns on safe and average subject to many arb itrary assumptions such as the ri sk assets) has long played a central rol e in finance. 11 releva nt period for tak in g an average. Compound ing is a key factor in asset allocation decisions to determine the difficulty or usi ng historical returns is the we ll the portfolio mi x of debt and equity instruments. noted fa ct that stand ard model s or consum er choice Moreover, the market ri sk premium plays a critica l ro le would predi ct much lower spreads between equity and in th e Capital Asset Pricing Model (CAPM ), the most debt returns than have occurred in US markets- the widely used means of estimating equity hurdle rates by so ca lled equity risk premium puzzle (sec Welch, 2000 practitioners. -
Capital Adequacy Requirements (CAR)
Guideline Subject: Capital Adequacy Requirements (CAR) Chapter 3 – Credit Risk – Standardized Approach Effective Date: November 2017 / January 20181 The Capital Adequacy Requirements (CAR) for banks (including federal credit unions), bank holding companies, federally regulated trust companies, federally regulated loan companies and cooperative retail associations are set out in nine chapters, each of which has been issued as a separate document. This document, Chapter 3 – Credit Risk – Standardized Approach, should be read in conjunction with the other CAR chapters which include: Chapter 1 Overview Chapter 2 Definition of Capital Chapter 3 Credit Risk – Standardized Approach Chapter 4 Settlement and Counterparty Risk Chapter 5 Credit Risk Mitigation Chapter 6 Credit Risk- Internal Ratings Based Approach Chapter 7 Structured Credit Products Chapter 8 Operational Risk Chapter 9 Market Risk 1 For institutions with a fiscal year ending October 31 or December 31, respectively Banks/BHC/T&L/CRA Credit Risk-Standardized Approach November 2017 Chapter 3 - Page 1 Table of Contents 3.1. Risk Weight Categories ............................................................................................. 4 3.1.1. Claims on sovereigns ............................................................................... 4 3.1.2. Claims on unrated sovereigns ................................................................. 5 3.1.3. Claims on non-central government public sector entities (PSEs) ........... 5 3.1.4. Claims on multilateral development banks (MDBs)